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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 4926–4950 of 9051 papers

TitleStatusHype
Recover from Horcrux: A Spectrogram Augmentation Method for Cardiac Feature Monitoring from Radar Signal Components—0
Rectified Flow For Structure Based Drug Design—0
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation—0
Recurrent and Contextual Models for Visual Question Answering—0
Recurring Concept Meta-learning for Evolving Data Streams—0
Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization—0
Reddit: A Gold Mine for Personality Prediction—0
ReDDiT: Rehashing Noise for Discrete Visual Generation—0
Redrawing attendance boundaries to promote racial and ethnic diversity in elementary schools—0
Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games—0
Reducing Diversity to Generate Hierarchical Archetypes—0
Reducing false positives in strong lens detection through effective augmentation and ensemble learning—0
Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity—0
Reducing Popularity Bias in Recommendation Over Time—0
Reducing the Mutual Outage Probability of Cooperative Non-Orthogonal Multiple Access—0
Reducing the Scope of Language Models—0
Redundancy Aware Multi-Reference Based Gainwise Evaluation of Extractive Summarization—0
Label-Based Diversity Measure Among Hidden Units of Deep Neural Networks: A Regularization Method—0
ReelFramer: Human-AI Co-Creation for News-to-Video Translation—0
Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form Text—0
Self-paced Multi-grained Cross-modal Interaction Modeling for Referring Expression Comprehension—0
Regional Adversarial Training for Better Robust Generalization—0
Region-level Active Detector Learning—0
Regularized Attentive Capsule Network for Overlapped Relation Extraction—0
Regularized directional representations for medical image registration—0
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